{
 "cells": [
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "# 皮尔逊相关系数法",
   "id": "ab33d2d8f4b9bbd9"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-08T05:44:17.654671Z",
     "start_time": "2025-10-08T05:44:17.652672Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import pandas as pd\n",
    "from sklearn.preprocessing import StandardScaler"
   ],
   "id": "836faddaf8c3d42d",
   "outputs": [],
   "execution_count": 6
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-08T05:44:56.107956Z",
     "start_time": "2025-10-08T05:44:56.102152Z"
    }
   },
   "cell_type": "code",
   "source": [
    "advertising = pd.read_csv('../data/advertising.csv')\n",
    "print(advertising.shape)\n",
    "print(advertising.head())\n",
    "print(advertising.columns[0])\n",
    "advertising.drop(advertising.columns[0], axis=1, inplace=True)\n",
    "print(advertising.head())"
   ],
   "id": "e191a5c895529c7c",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(200, 5)\n",
      "   Unnamed: 0     TV  Radio  Newspaper  Sales\n",
      "0           1  230.1   37.8       69.2   22.1\n",
      "1           2   44.5   39.3       45.1   10.4\n",
      "2           3   17.2   45.9       69.3    9.3\n",
      "3           4  151.5   41.3       58.5   18.5\n",
      "4           5  180.8   10.8       58.4   12.9\n",
      "Unnamed: 0\n",
      "      TV  Radio  Newspaper  Sales\n",
      "0  230.1   37.8       69.2   22.1\n",
      "1   44.5   39.3       45.1   10.4\n",
      "2   17.2   45.9       69.3    9.3\n",
      "3  151.5   41.3       58.5   18.5\n",
      "4  180.8   10.8       58.4   12.9\n"
     ]
    }
   ],
   "execution_count": 9
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-08T05:49:04.423364Z",
     "start_time": "2025-10-08T05:49:04.420788Z"
    }
   },
   "cell_type": "code",
   "source": [
    "X = advertising.drop('Sales', axis=1)\n",
    "y = advertising['Sales']\n",
    "print(X.shape, y.shape)"
   ],
   "id": "98d6ae382b549da6",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(200, 3) (200,)\n"
     ]
    }
   ],
   "execution_count": 12
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-08T05:58:40.718420Z",
     "start_time": "2025-10-08T05:58:40.714101Z"
    }
   },
   "cell_type": "code",
   "source": [
    "X_corr = X.corrwith(y, method='pearson')\n",
    "print(X_corr) # 计算每个特征与目标变量的皮尔逊相关系数\n",
    "X_corr_bool = X_corr.abs() > 0.5 # 选择相关系数绝对值大于0.5的特征\n",
    "print(X_corr_bool)\n",
    "X_selected = X.loc[:, X_corr_bool] # 选择相关系数绝对值大于0.5的特征\n",
    "print(X_selected.shape)"
   ],
   "id": "9d0d84d5fe36e2bc",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TV           0.782224\n",
      "Radio        0.576223\n",
      "Newspaper    0.228299\n",
      "dtype: float64\n",
      "TV            True\n",
      "Radio         True\n",
      "Newspaper    False\n",
      "dtype: bool\n",
      "(200, 2)\n"
     ]
    }
   ],
   "execution_count": 22
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-08T06:00:18.215154Z",
     "start_time": "2025-10-08T06:00:18.212921Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ],
   "id": "c85ddab67a61472a",
   "outputs": [],
   "execution_count": 24
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-08T06:03:53.739863Z",
     "start_time": "2025-10-08T06:03:53.682207Z"
    }
   },
   "cell_type": "code",
   "source": [
    "corr_matrix = advertising.corr()\n",
    "sns.heatmap(corr_matrix, annot=True, cmap='coolwarm', fmt='.2f')\n",
    "plt.title('Correlation Matrix')\n",
    "plt.show()"
   ],
   "id": "38c4ac2eddbf49f3",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 28
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
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